Reduce exposure to claims fraud with integration of public records

Transcription

1 White Paper Reduce exposure to claims fraud with integration of public records January 2014 Risk Solutions Health Care

2 Introduction The United States now spends about $2.6 trillion annually on health care (17.5 percent of GDP) and with the reform initiatives under the Affordable Care Act (ACA), the number of Americans covered and the amount spent will grow dramatically, potentially leading to even greater fraud, waste and abuse in the system. The U.S. Department of Health and Human Services (HHS) estimated that, in 2013, it improperly spent about $65 billion in taxpayer funds through waste, errors and fraud a figure that was primarily fueled by an estimated $60 billion in overpayments to Medicare and Medicaid. 1 According to the Health Care Cost Institute (HCCI), costs between 2010 and 2011 alone rose 4.6 percent, a 21 percent increase from the previous year. In 2008, it was reported that Medicare spent less than two tenths of a cent of every dollar of its $456 billion annual budget combating fraud, waste and abuse (FWA). These statistics represent avoidable health care costs that directly impact the cost and quality of health care for every American. Health care fraud and abuse not only contributes to higher insurance premiums; every dollar spent on fraudulent or abusive claims reduces the amount of money available to improve the quality of care for those incurring legitimate expenses. Models for how to address FWA in the American health care system are not new, and many have been around for two decades or more. However, due to the rapidly changing environment, increase in remote technology for claims submission and payments, and other factors, new ideas and methods are beginning to take hold. One of these is the incorporation of non-health care related data, such as publically available records. The U.S. Department of Health and Human Services (HHS) estimated that, in 2013, it improperly spent about $65 billion in taxpayer funds through waste, errors and fraud a figure that was primarily fueled by an estimated $60 billion in overpayments to Medicare and Medicaid. 1 How Recent Changes in the Health Care System can Affect FWA While it is unclear what the final version of this iteration of health care reform will look like when the dust settles, what is known is that money paid for fraudulent or abusive claims is money not spent on the delivery of quality care. This is simply not acceptable. How FWA is Commonly Addressed Today Most payers today utilize a post-payment method for detection, analysis, investigation and the decisioning of claims and related providers. Although the industry is gradually moving the detection further upstream into prepay, the vast majority still rely on a post-payment system. The standard method is to wait days after claims have been made to review the paid claims data, often utilizing various tools such as data warehousing, rules-based detection sources, reporting tools and others. The paid claims 1 and-medicaid-overpayments 1

3 are run through these tools in order to help the investigator determine if further research or action is necessary. Since the inherent nature of FWA is not black and white, it is often difficult to determine if further punitive action is needed, such as denying a claim; placing the provider on pre-pay review for all subsequent, like claims; withholding future payments; or more stringent actions such as prosecution. Claims data is typically the sole source from which Special Investigation Units (SIU) and others mine their data to identify overpayments, regardless of whether or not the organization is using it in pre-pay, post-pay detection or provider and hospital audit. This data is often fragmented, incomplete and, in some cases, inaccurate. While the claims will always be the primary source of seeking overpayments, other data can be infused into the process in order to generate more accurate leads and provide the investigator with a greater sense of certainty about pursuing further. New Models and the Value of Public Records Data One thing is clear traditional methods alone are not adequate to face the ever changing and more complex schemes and methods. Leaders and decision makers need to question whether the tools they have allocated to combat today s health care FWA are still effective for countering today s risks. Public records, including provider licensure, criminal background and death records, have been part of an SIU investigator s tool kit for some time. However, the process to search and acquire the records has been highly laborious and time consuming. An investigator would travel to or call each source of the public record and request and review the information. It could take days, weeks and possibly months to find the information the investigator was looking for. And even then, synching the records from various sources proved time-consuming and fraught with error and inconsistencies. In the late 1970s and early 1980s, public records holders began storing this information electronically. As technology and computers advanced, the aggregation and dissemination of these public records became more readily available and, as such, they were leveraged on a more common and frequent basis. One of the first to embrace the new retrieval method was the investigative divisions of law enforcement agencies who recognized the immense value of public records. In health care, widespread adoption was slow. That is until now. Using public records to enhance FWA results found in claims takes a proactive approach to uncovering derogatory attributes linked to providers and other individuals interacting across the health care system, reducing a payer s exposure to fraud and abuse before it affects the organization s bottom line, regulatory compliance and patient safety. Using public records to enhance FWA results found in claims takes a proactive approach to uncovering derogatory attributes linked to providers and other individuals interacting across the health care system, reducing a payer s exposure to fraud and abuse before it affects the organization s bottom line, regulatory compliance and patient safety. Public records provide insight into an individual s background that may not ever be of notice but should be. Drawn from thousands of data sources, the information that can be aggregated and analyzed provides an amazing 2

4 opportunity to understand the risk triggers and possible motives for aberrant behaviors of individuals interacting within the health care ecosystem. When incorporated appropriately within the FWA program, public records can leverage advanced data technology to assist health care payers in verifying and monitoring health care provider licensing and credentials, and detecting and preventing fraudulent or criminal provider activity. For example, sometimes it isn t what s there that is important, but rather what is not there. A recent analysis of a national health care payer s claims data illustrated the risk. It s bad enough to find a provider who billed $2 million in a single year (and was paid more than $600,000) without any medical licensure in the state in which he appeared to practice. And while it s worse to find no medical training or licensure anywhere in the country for the provider, the real bad news is to find no other data for the individual at all up to and including no name match. It wouldn t be the first time that fictional characters have siphoned money from the health care system, and it won t be the last unless public records are integrated into fraud detection protocols. In another example, LexisNexis worked with a western state to conduct a record screening against its complete active provider file. The screening uncovered several derogatory indicators within the file, such as deceased providers, risky financial behavior and license issues. However, the top four most egregious findings, below, were discovered when comparing the provider file against public criminal records. A urologist was found guilty in 1999 of a felony charge for disorderly conduct and a weapon possession. This provider received over $500,000 from the state after the felony conviction. A pediatrician was found guilty in 2007 of a felony charge for unlawful dispensing of drugs in an eastern state. The provider relocated to the west, continued practicing and received just under $1 million from the state after the felony conviction. An emergency room physician was found guilty in 2004 of a felony charge involving narcotics. This provider continued receiving payments for services rendered from the state after the conviction approximately $300,000 in total. A pediatrician was arrested on criminal charges in Prior to adjudication (a different state was prosecuting him for another reason), he pled guilty in the state court system. Unfortunately, after the guilty plea, this provider received approximately $1.6 million for services. A recent analysis of a national health care payer s claims data illustrated the risk. It s bad enough to find a provider who billed $2 million in a single year (and was paid more than $600,000) without any medical licensure in the state in which he appeared to practice. The infusion of public records information can provide guidance that not only helps prioritize a list of providers for further scrutiny, but also spotlights the extreme bad actors in a program provider file. 3

5 This also increases the ability to efficiently process multiple searches and obtain the critical information contained within massive volumes of data. Public records can be utilized in either pre- or post-pay detection to determine if suspect providers have other issues that, combined with aberrancies found in their claim data, raise suspicion of inappropriate treat mentor billing. Some of the issues that can be detected with public records include: Deceased providers License status Sanctions both state and specialty boards Criminal convictions High risk indicators for address and SSN Financial information such as liens, bankruptcies and judgments Provider business ID verification While the public records, in and of themselves, may not warrant the denial of a claim, or provide reason enough for investigation, they can help to strengthen the case and provide greater assurance that the provider in question should be looked into further. Payers will achieve greater efficiency and productivity when public records are integrated into their FWA program along with the core claims detection. Conclusion Payers will achieve greater efficiency and productivity when public records are integrated into their fraud, waste and abuse program along with the core claims detection. By combining the public records with claims results, payers can more accurately identify viable claims and providers, and more importantly, hone in on those that are most likely to reduce positive results for the organization. This also helps to reduce the time spent on lower priority events which may not net results, as well as those red herrings which waste time. Combined, this enables the SIU to increase savings and recoveries, while creating efficiencies with scarce resources. 4

6 For more information: Call or visit About LexisNexis Risk Solutions LexisNexis Risk Solutions ( is a leader in providing essential information that helps customers across all industries and government predict, assess and manage risk. Combining high-performance cluster computing, unparalleled stores of public data and social networking and predictive analytics, we provide products and services that address evolving client needs in the risk sector while upholding the highest standards of security and privacy. LexisNexis Risk Solutions is part of Reed Elsevier, a leading publisher and information provider that serves customers in more than 100 countries with more than 30,000 employees worldwide. Our health care solutions assist payers, providers and business partners with ensuring appropriate access to health care data and programs, enhancing disease management contact ratios, improving operational processes and proactively combating fraud, waste and abuse across the continuum. Due to the nature of the origin of public record information, the public records and commercially available data sources used in reports may contain errors. Source data is sometimes reported or entered inaccurately, processed poorly or incorrectly, and is generally not free from defect. This product or service aggregates and reports data, as provided by the public records and commercially available data sources, and is not the source of the data, nor is it a comprehensive compilation of the data. Before relying on any data, it should be independently verified. LexisNexis and the Knowledge Burst logo are registered trademarks of Reed Elsevier Properties Inc., used under license. Other products and services may be trademarks or registered trademarks of their respective companies. Copyright 2014 LexisNexis. All rights reserved. NXR EN-US